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Ecological monitoring of terrestrial ecosystem recovery from man-made perturbation: assessing community complexity

机译:人造扰动陆地生态系统回收的生态监测:评估群落复杂性

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The dynamics of ecological complexity are presented from an area severely damaged by air pollution to understand the effect of perturbation intensity on long-term recovery dynamics of forest communities. Perturbation is assumed to be most intense near the smelter and to decrease with distance. Complexity is assessed using Shannon entropy as well as a contemporary measure of structural complexity. We find that while total complexity and diversity increase with decreasing perturbation intensity, structural complexity does not. It is also uncovered that community-level dynamics are more predictable than species-level dynamics. The data were analyzed using multivariate methods to determine how spatial pattern and groupings produce trends in community-level dynamics. The perturbation gradient is characterized by a continuum of understory communities with colonizing and metal-tolerant species proximal to the pollution source and sensitive species at distal sites. The overstory community mimicked this pattern, but vertical structure was found to be important in characterizing the gradient. Ecological monitoring of the multi-level effects of pollution on ecosystems is important for understanding the full implications of multiple stressors in the environment.
机译:生态复杂性的动态来自于空气污染严重受损的区域,以了解扰动强度对森林社区长期恢复动态的影响。假设扰动在冶炼厂附近最强烈并随着距离减少。使用Shannon Entropy评估复杂性以及当代结构复杂性的衡量标准。我们发现,虽然总复杂性和多样性随着扰动强度的降低而增加,但结构复杂性没有。它还发现,社区级动态比物种级动态更可预测。使用多变量方法分析数据,以确定空间模式和分组如何产生社区级动态的趋势。扰动梯度的特征在于林下社区的连续组,具有近端的植物和金属耐受物种,在远端位点处的敏感物种。过流社区模仿这种模式,但发现垂直结构在表征梯度方面很重要。对生态系统污染的多级效应的生态监测对于了解多种压力源在环境中的全面影响是重要的。

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